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            <h1 id="seo-header">cellphoneDB (一) 使用流程</h1>
            
            
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                <h2 id="第一步-导出数据"><a href="#第一步-导出数据" class="headerlink" title="第一步 导出数据"></a>第一步 导出数据</h2><figure class="highlight pgsql"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br></pre></td><td class="code"><pre><code class="hljs pgsql">f_prepare4cellphoneDB &lt;- <span class="hljs-keyword">function</span>(lc_scRNA, lc_dir, lc_className)&#123;<br>    <span class="hljs-keyword">if</span> (!file.<span class="hljs-keyword">exists</span>(lc_dir))&#123;dir.<span class="hljs-keyword">create</span>(lc_dir)&#125;<br>    # 生成 count.txt <br>    <span class="hljs-keyword">write</span>.<span class="hljs-keyword">table</span>(<span class="hljs-keyword">as</span>.matrix(lc_scRNA@assays$RNA@data), file.path(lc_dir,<span class="hljs-string">&#x27;cellphonedb_count.txt&#x27;</span>), sep=<span class="hljs-string">&#x27;\t&#x27;</span>, <span class="hljs-keyword">quote</span>=F)<br>    # 生成 meta.txt<br>    lc_meta_data &lt;- cbind(rownames(lc_scRNA@meta.data), lc_scRNA@meta.data[, lc_className, <span class="hljs-keyword">drop</span>=F])<br>    lc_meta_data &lt;- <span class="hljs-keyword">as</span>.matrix(lc_meta_data)<br>    lc_meta_data[<span class="hljs-keyword">is</span>.na(lc_meta_data)] = &quot;Unkown&quot; #  细胞类型中不能有NA<br>    <span class="hljs-keyword">write</span>.<span class="hljs-keyword">table</span>(lc_meta_data, file.path(lc_dir,<span class="hljs-string">&#x27;cellphonedb_meta.txt&#x27;</span>), sep=<span class="hljs-string">&#x27;\t&#x27;</span>, <span class="hljs-keyword">quote</span>=F, <span class="hljs-keyword">row</span>.names=F)<br>&#125;<br>f_prepare4cellphoneDB(sc_Neuron,&quot;Neuron&quot;, &quot;hmca_class&quot;)<br>f_prepare4cellphoneDB(sc_Neuron,&quot;Neuron_br&quot;, &quot;orig.ident&quot;)<br></code></pre></td></tr></table></figure>

<h2 id="第二步-提交运算"><a href="#第二步-提交运算" class="headerlink" title="第二步 提交运算"></a>第二步 提交运算</h2><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br></pre></td><td class="code"><pre><code class="hljs bash"><span class="hljs-meta">#!/bin/bash</span><br><span class="hljs-comment">#PBS -q batch</span><br><span class="hljs-comment">#PBS -V</span><br><span class="hljs-comment">#PBS -o /home/rqzhang/cellphonedb.out</span><br><span class="hljs-comment">#PBS -e /home/rqzhang/cellphonedb.err</span><br><span class="hljs-comment">#PBS -l nodes=1:ppn=32</span><br><span class="hljs-comment">#PBS -r y</span><br> <br><span class="hljs-built_in">cd</span> /home/rqzhang/zlliu/R_data/21.10.01.10x/Neuron<br>cellphonedb method statistical_analysis  cellphonedb_meta.txt  cellphonedb_count.txt --counts-data=gene_name  --threads=32<br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta.txt<br><br><span class="hljs-built_in">cd</span> /home/rqzhang/zlliu/R_data/21.10.01.10x/Neuron_br<br>cellphonedb method statistical_analysis  cellphonedb_meta.txt  cellphonedb_count.txt --counts-data=gene_name  --threads=32<br>cellphonedb plot dot_plot<br>cellphonedb plot heatmap_plot cellphonedb_meta.txt<br><br></code></pre></td></tr></table></figure>

<h2 id="第三步-可视化"><a href="#第三步-可视化" class="headerlink" title="第三步 可视化"></a>第三步 可视化</h2><figure class="highlight routeros"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br><span class="line">58</span><br><span class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br><span class="line">70</span><br><span class="line">71</span><br><span class="line">72</span><br><span class="line">73</span><br><span class="line">74</span><br><span class="line">75</span><br><span class="line">76</span><br><span class="line">77</span><br><span class="line">78</span><br><span class="line">79</span><br><span class="line">80</span><br><span class="line">81</span><br><span class="line">82</span><br><span class="line">83</span><br><span class="line">84</span><br><span class="line">85</span><br><span class="line">86</span><br><span class="line">87</span><br><span class="line">88</span><br><span class="line">89</span><br><span class="line">90</span><br><span class="line">91</span><br><span class="line">92</span><br><span class="line">93</span><br><span class="line">94</span><br><span class="line">95</span><br></pre></td><td class="code"><pre><code class="hljs routeros">f_image_output &lt;- function(fileName, image, <span class="hljs-attribute">width</span>=1920, <span class="hljs-attribute">height</span>=1080, <span class="hljs-attribute">lc_pdf</span>=T, <span class="hljs-attribute">lc_resolution</span>=72)&#123;<br>    <span class="hljs-keyword">if</span>(lc_pdf)&#123;<br>        width = width / lc_resolution<br>        height = height / lc_resolution<br>        pdf(paste(fileName, <span class="hljs-string">&quot;.pdf&quot;</span>, <span class="hljs-attribute">sep</span>=<span class="hljs-string">&quot;&quot;</span>), width = width, height = height)<br>    &#125;<span class="hljs-keyword">else</span>&#123;<br>        png(paste(fileName, <span class="hljs-string">&quot;.png&quot;</span>, <span class="hljs-attribute">sep</span>=<span class="hljs-string">&quot;&quot;</span>), width = width, height = height)<br>    &#125;<br>    <span class="hljs-built_in">print</span>(image)<br>    dev.off()<br>&#125;<br><br><span class="hljs-comment"># Rearrange data column sequence</span><br>library(dplyr)<br>f_cDB_order_sequence &lt;- function(lc_df)&#123;<br>    da &lt;- data.frame()<br>    df &lt;- subset(lc_df, receptor_a == <span class="hljs-string">&#x27;True&#x27;</span> &amp; receptor_b == <span class="hljs-string">&#x27;False&#x27;</span>  receptor_a == <span class="hljs-string">&#x27;False&#x27;</span> &amp; receptor_b == <span class="hljs-string">&#x27;True&#x27;</span>)<br>    <span class="hljs-keyword">for</span>(i <span class="hljs-keyword">in</span> 1:length(df<span class="hljs-variable">$gene_a</span>))&#123;<br>    sub_data &lt;- df[i, ]<br>    <span class="hljs-keyword">if</span>(sub_data<span class="hljs-variable">$receptor_b</span>==<span class="hljs-string">&#x27;False&#x27;</span>)&#123;<br>        <span class="hljs-keyword">if</span>(sub_data<span class="hljs-variable">$receptor_a</span>==<span class="hljs-string">&#x27;True&#x27;</span>)&#123;<br>            old_names &lt;- colnames(sub_data)<br>            my_list &lt;- strsplit(old_names[-c(1:11)], <span class="hljs-attribute">split</span>=<span class="hljs-string">&quot;\\&quot;</span>)<br>            my_character &lt;- paste(sapply(my_list, <span class="hljs-string">&#x27;[[&#x27;</span>, 2L), sapply(my_list, <span class="hljs-string">&#x27;[[&#x27;</span>, 1L), <span class="hljs-attribute">sep</span>=<span class="hljs-string">&#x27;&#x27;</span>)<br>            new_names &lt;- c(names(sub_data)[1:4], <span class="hljs-string">&#x27;gene_b&#x27;</span>, <span class="hljs-string">&#x27;gene_a&#x27;</span>, <span class="hljs-string">&#x27;secreted&#x27;</span>, <span class="hljs-string">&#x27;receptor_b&#x27;</span>, <span class="hljs-string">&#x27;receptor_a&#x27;</span>, <span class="hljs-string">&quot;annotation_strategy&quot;</span>, <span class="hljs-string">&quot;is_integrin&quot;</span>, my_character)<br>            sub_data = dplyr::select(sub_data, new_names)<br>            # <span class="hljs-built_in">print</span>(<span class="hljs-string">&#x27;Change sequence!!!&#x27;</span>)<br>            names(sub_data) &lt;- old_names<br>            da = rbind(da, sub_data) <br>        &#125;<br>    &#125;<span class="hljs-keyword">else</span>&#123;<br>            da = rbind(da, sub_data)<br>    &#125;<br>    &#125;<br>    return(da)<br>&#125;<br><br>f_cDB_mergePandM &lt;- function(means_order, pvals_order)&#123;<br>    means_sub &lt;- means_order[, c(<span class="hljs-string">&#x27;interacting_pair&#x27;</span>, colnames(means_order)[-c(1:11)])]<br>    pvals_sub &lt;- pvals_order[, c(<span class="hljs-string">&#x27;interacting_pair&#x27;</span>, colnames(means_order)[-c(1:11)])]<br>    means_gather &lt;- tidyr::gather(means_sub, celltype, mean_expression, names(means_sub)[-1])<br>    pvals_gather &lt;- tidyr::gather(pvals_sub, celltype, pval, names(pvals_sub)[-1])<br>    mean_pval &lt;- dplyr::left_join(means_gather, pvals_gather, by = c(<span class="hljs-string">&#x27;interacting_pair&#x27;</span>, <span class="hljs-string">&#x27;celltype&#x27;</span>))<br>    mean_pval<br>&#125;<br><br>f_readcellphoneDB &lt;- function(lc_dir)&#123;<br>    res = list()<br>    res<span class="hljs-variable">$pvals</span> &lt;- f_cDB_order_sequence(read.delim(file.path(lc_dir, <span class="hljs-string">&quot;out&quot;</span>,<span class="hljs-string">&quot;pvalues.txt&quot;</span>), check.names = <span class="hljs-literal">FALSE</span>))<br>    res<span class="hljs-variable">$means</span> &lt;- f_cDB_order_sequence(read.delim(file.path(lc_dir, <span class="hljs-string">&quot;out&quot;</span>, <span class="hljs-string">&quot;means.txt&quot;</span>), check.names = <span class="hljs-literal">FALSE</span>))<br>    res<span class="hljs-variable">$s_means</span> &lt;- read.delim(file.path(lc_dir, <span class="hljs-string">&quot;out&quot;</span>, <span class="hljs-string">&quot;significant_means.txt&quot;</span>), check.names = <span class="hljs-literal">FALSE</span>)<br>    res<span class="hljs-variable">$m_p</span> &lt;- f_cDB_mergePandM(res<span class="hljs-variable">$means</span>, res<span class="hljs-variable">$pvals</span>)<br>    lc_tp &lt;- res<span class="hljs-variable">$m_p</span> %&gt;% dplyr::select(interacting_pair, celltype, pval) %&gt;% tidyr::spread(<span class="hljs-attribute">key</span>=celltype, <span class="hljs-attribute">value</span>=pval)<br>    lc_sig_pairs &lt;- lc_tp[which(rowSums(lc_tp&lt;=0.05)!=0), ]<br>    res<span class="hljs-variable">$s_m_p</span> &lt;- subset(res<span class="hljs-variable">$m_p</span>, interacting_pair %<span class="hljs-keyword">in</span>% lc_sig_pairs<span class="hljs-variable">$interacting_pair</span>)<br>    res<br>&#125;<br><br>f_cDB_dotplot &lt;- function(lc_m_p)&#123;<br>    lc_m_p %&gt;% ggplot(aes(<span class="hljs-attribute">x</span>=interacting_pair, <span class="hljs-attribute">y</span>=celltype)) +<br>    # geom_point(aes(<span class="hljs-attribute">color</span>=log2(mean_expression), <span class="hljs-attribute">size</span>=pval)) +<br>    # scale_size(trans = <span class="hljs-string">&#x27;reverse&#x27;</span>) +<br>    geom_point(aes(<span class="hljs-attribute">color</span>=log2(mean_expression), <span class="hljs-attribute">size</span>=-log10(pval+1*10^-3)) ) +<br>    guides(colour = guide_colourbar(order = 1),size = guide_legend(order = 2)) +<br>    labs(<span class="hljs-attribute">x</span>=<span class="hljs-string">&#x27;&#x27;</span>, <span class="hljs-attribute">y</span>=<span class="hljs-string">&#x27;&#x27;</span>) +<br>    scale_color_gradientn(<span class="hljs-attribute">name</span>=<span class="hljs-string">&#x27;Expression level \n(log2 mean expression \nmolecule1, molecule2)&#x27;</span>, colours = terrain.colors(100)) +<br>    # scale_color_gradient2(<span class="hljs-string">&#x27;Expression level \n(log2 mean expression \nmolecule1, molecule2)&#x27;</span>, low = <span class="hljs-string">&#x27;blue&#x27;</span>, mid = <span class="hljs-string">&#x27;yellow&#x27;</span>, high = <span class="hljs-string">&#x27;red&#x27;</span>) +<br>    theme(axis.text.x= element_text(<span class="hljs-attribute">angle</span>=45, <span class="hljs-attribute">hjust</span>=1)) +<br>    # coord_flip() +<br>    theme(<br>    panel.border = element_rect(color = <span class="hljs-string">&#x27;black&#x27;</span>, fill = NA),<br>    panel.grid.major.x = element_blank(),<br>    panel.grid.major.y = element_blank(),<br>    panel.grid.minor.x = element_blank(),<br>    panel.grid.minor.y = element_blank(),<br>    panel.background   = element_blank(),<br>    axis.title.x       = element_blank(),<br>    axis.title.y       = element_blank(),<br>    axis.ticks         = element_blank()<br>    # plot.title         = element_text(hjust = 0.5),<br>    # legend.position = <span class="hljs-string">&#x27;bottom&#x27;</span> # guides(fill = guide_legend(label.position = <span class="hljs-string">&quot;bottom&quot;</span>))<br>    # legend.position    = <span class="hljs-string">&quot;bottom&quot;</span><br>    # axis.text.y.right  = element_text(<span class="hljs-attribute">angle</span>=270, <span class="hljs-attribute">hjust</span>=0.5)<br>    ) +<br>    theme(legend.key.size = unit(0.4, <span class="hljs-string">&#x27;cm&#x27;</span>), #change legend key size<br>    # legend.key.height = unit(1, <span class="hljs-string">&#x27;cm&#x27;</span>), #change legend key height<br>    # legend.key.width = unit(1, <span class="hljs-string">&#x27;cm&#x27;</span>), #change legend key width<br>    legend.title = element_text(<span class="hljs-attribute">size</span>=9), #change legend title font size<br>    legend.text = element_text(<span class="hljs-attribute">size</span>=8)) #change legend text font size<br>&#125;<br><br>br_d &lt;- f_readcellphoneDB(<span class="hljs-string">&#x27;Neuron_br&#x27;</span>)<br>tp_img &lt;- f_cDB_dotplot(subset(br_d <span class="hljs-variable">$s_m_p</span>, pval&lt;0.05))<br>f_image_output(<span class="hljs-string">&#x27;Neuron_br&#x27;</span>,tp_img, width = 1080,height = 1080)<br><br></code></pre></td></tr></table></figure>
                
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